Developing a molecular diagnostic model for heatstroke-induced coagulopathy: a proteomics and metabolomics approach
The study uncovered critical metabolic and protein changes linked to heatstroke, highlighting the involvement of energy regulation, lipid metabolism, and carbohydrate metabolism. Building on these findings, an optimal machine learning diagnostic model was developed to boost the accuracy of HSIC diagnosis, integrating LDHA, NGAL, prothrombin, and GBE as key biomarkers.
Authors
- Jingchun Song (ORCID: https://orcid.org/0000-0001-5869-5077)
- Lincui Zhong (ORCID: https://orcid.org/0000-0001-5463-8745)
- Qingbo Zeng (ORCID: https://orcid.org/0000-0002-0742-125X)
- Nianqing Zhang
- Longping He (ORCID: https://orcid.org/0000-0002-4307-0733)
- Qingwei Lin
- Xingping Deng
- Ye Zhou (ORCID: https://orcid.org/0000-0001-9367-7608)
- Qing Song (ORCID: https://orcid.org/0000-0001-7447-0388)
Institutions
- Chinese PLA General Hospital (CN)
- People's Liberation Army 401 Hospital (CN)
- Sanya University (CN)
- Anyang Hospital of Traditional Chinese Medicine (CN)
Publication Details
- Journal
- Frontiers in Molecular Biosciences
- Published
- 2025-06-20
- DOI
- https://doi.org/10.3389/fmolb.2025.1616073
- Citations
- 1
- Primary Topic
- Climate Change and Health Impacts
- Type
- article
- Field-Weighted Citation Impact
- 1.20